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Jul 5, 2026, 9:37:04 AMJul 5
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About NORMA
NORMA 2027 is the Nordic Mathematics Education Conference. The NORMA conferences are organized in collaboration with NoRME— the Nordic Society for Research in Mathematics Education, https://sites.google.com/view/norme/home, NoRME is open for membership from national societies for research in mathematics education in the Nordic and Baltic countries.
The NORMA conferences offer forum for discussions and constructive interactions among researchers, teachers, teacher educators, graduate students and others interested in mathematics education research in the Nordic and Baltic context. NORMA are small-scale conferences that emphasize interaction between participants and interplay between scientific and social activities. NORMA 27 will have a limit of 380 participants. The conference language is English and all presentations will be in English. The scientific program and the review process are organized and managed by the international program committee (IPC) for NORMA 27.
Tentative agenda of the multi-track conference:Tuesday, June 8 - Thursday noon, June 11: the main conference
Thursday afternoon, June 11: school visits, social programme (optional)
The conference theme
(No) Tradeoffs Between Human and Machine Intelligence in Mathematics Education
Recent advances in artificial intelligence (AI) and machine learning (ML) are rapidly transforming educational ecosystems, reshaping how mathematical knowledge is constructed, communicated, and assessed. From adaptive learning systems and intelligent tutoring to automated feedback and generative models capable of solution synthesis, machine intelligence promises unparalleled affordances for personalization and scalability. At the same time, concerns about algorithmic opacity, epistemic displacement, and unintended impacts on students' conceptual understanding foreground enduring questions about the role of human agency, teacher expertise, and collective mathematical practices (Heffernan & Heffernan, 2014; Holmes, Bialik & Fadel, 2019). The proposed theme invites the Nordic-Baltic mathematics education research community to explore whether and how human and machine intelligence can be mutually reinforcing rather than in tension. Instead of framing the relationship as a zero-sum game where gains in machine support undermine human pedagogical authority or cognitive engagement, this theme foregrounds the interplay and co-construction of competencies, pedagogies, and technologies that honor the distinct yet complementary strengths of shared human-machine cognition, where human is always in the loop as a decision-maker. This dialogue is timely: contemporary research suggests that AI-augmented learning environments can support individualized scaffolding (Spiteri & Dingli, 2025), yet meaningful learning and mathematical agency remain grounded in human interpretation, negotiation, and social reasoning (Noss & Hoyles, 1996; Kirschner et al., 2011).
For NORMA 2027, we define machine intelligence broadly, encompassing not only widely used AI chatbots/LLMs, but also adaptive learning systems involving algorithmically informed analytics, intelligent feedback mechanisms, and data-informed personalisation. Human intelligence encompasses individual and collective sense-making, teacher professional judgment, and culturally situated mathematical practices. The conference invites research that articulates theoretical framings, empirical insights, and design principles that transcend simplistic 'tradeoff' narratives to foreground synergies, tensions, affordances, and constraints in mathematics education in the AI era.
Mathematics education has historically engaged with technological innovations—from calculators and dynamic geometry environments to intelligent tutoring systems—raising persistent questions about what and how students learn. For example, research on computer-based tools underscores the importance of instrumental orchestration and teacher mediation in technology-rich contexts (Drijvers, 2003; Trouche, 2004). As systems become increasingly autonomous and generative, similar questions arise about who holds epistemic authority and how students develop mathematical reasoning rather than algorithmic mimicry (Hod & Karp, 2023). Critical perspectives also highlight ethical and equity considerations in AI deployment (Ee & Choi, 2021), challenging researchers to articulate frameworks that integrate technological innovation with pedagogical integrity.
The overarching ambition of NORMA 2027 is to negotiate an inspiring research agenda that moves beyond simplistic dichotomies between human and machine intelligence in Nordic and Baltic countries. By foregrounding collaboration, criticality, and constructivist sensibilities, this theme invites scholarship that reconceptualizes intelligence in mathematics education as distributed, situated, and co-constructed.
More: https://norma2027.tlu.ee/
NORMA 2027 is the Nordic Mathematics Education Conference. The NORMA conferences are organized in collaboration with NoRME— the Nordic Society for Research in Mathematics Education, https://sites.google.com/view/norme/home, NoRME is open for membership from national societies for research in mathematics education in the Nordic and Baltic countries.
The NORMA conferences offer forum for discussions and constructive interactions among researchers, teachers, teacher educators, graduate students and others interested in mathematics education research in the Nordic and Baltic context. NORMA are small-scale conferences that emphasize interaction between participants and interplay between scientific and social activities. NORMA 27 will have a limit of 380 participants. The conference language is English and all presentations will be in English. The scientific program and the review process are organized and managed by the international program committee (IPC) for NORMA 27.
Tentative agenda of the multi-track conference:Tuesday, June 8 - Thursday noon, June 11: the main conference
Thursday afternoon, June 11: school visits, social programme (optional)
The conference theme
(No) Tradeoffs Between Human and Machine Intelligence in Mathematics Education
Recent advances in artificial intelligence (AI) and machine learning (ML) are rapidly transforming educational ecosystems, reshaping how mathematical knowledge is constructed, communicated, and assessed. From adaptive learning systems and intelligent tutoring to automated feedback and generative models capable of solution synthesis, machine intelligence promises unparalleled affordances for personalization and scalability. At the same time, concerns about algorithmic opacity, epistemic displacement, and unintended impacts on students' conceptual understanding foreground enduring questions about the role of human agency, teacher expertise, and collective mathematical practices (Heffernan & Heffernan, 2014; Holmes, Bialik & Fadel, 2019). The proposed theme invites the Nordic-Baltic mathematics education research community to explore whether and how human and machine intelligence can be mutually reinforcing rather than in tension. Instead of framing the relationship as a zero-sum game where gains in machine support undermine human pedagogical authority or cognitive engagement, this theme foregrounds the interplay and co-construction of competencies, pedagogies, and technologies that honor the distinct yet complementary strengths of shared human-machine cognition, where human is always in the loop as a decision-maker. This dialogue is timely: contemporary research suggests that AI-augmented learning environments can support individualized scaffolding (Spiteri & Dingli, 2025), yet meaningful learning and mathematical agency remain grounded in human interpretation, negotiation, and social reasoning (Noss & Hoyles, 1996; Kirschner et al., 2011).
For NORMA 2027, we define machine intelligence broadly, encompassing not only widely used AI chatbots/LLMs, but also adaptive learning systems involving algorithmically informed analytics, intelligent feedback mechanisms, and data-informed personalisation. Human intelligence encompasses individual and collective sense-making, teacher professional judgment, and culturally situated mathematical practices. The conference invites research that articulates theoretical framings, empirical insights, and design principles that transcend simplistic 'tradeoff' narratives to foreground synergies, tensions, affordances, and constraints in mathematics education in the AI era.
Mathematics education has historically engaged with technological innovations—from calculators and dynamic geometry environments to intelligent tutoring systems—raising persistent questions about what and how students learn. For example, research on computer-based tools underscores the importance of instrumental orchestration and teacher mediation in technology-rich contexts (Drijvers, 2003; Trouche, 2004). As systems become increasingly autonomous and generative, similar questions arise about who holds epistemic authority and how students develop mathematical reasoning rather than algorithmic mimicry (Hod & Karp, 2023). Critical perspectives also highlight ethical and equity considerations in AI deployment (Ee & Choi, 2021), challenging researchers to articulate frameworks that integrate technological innovation with pedagogical integrity.
The overarching ambition of NORMA 2027 is to negotiate an inspiring research agenda that moves beyond simplistic dichotomies between human and machine intelligence in Nordic and Baltic countries. By foregrounding collaboration, criticality, and constructivist sensibilities, this theme invites scholarship that reconceptualizes intelligence in mathematics education as distributed, situated, and co-constructed.
More: https://norma2027.tlu.ee/
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